Abstract:

Recently, simultaneous wireless information and power transfer (SWIPT) using radio frequency (RF) waves has drawn an upsurge of research interest in various areas of communications, signal processing, and networking. SWIPT is considered as promising technology for practical energy-limited applications such as wireless sensor networks, wireless body networks, low-powered devices, internet of things (IoT), etc. Also, in the next generation wireless systems such as 5G, wireless RF energy harvesting is considered to be a promising solution to the energy scarcity issue. In the literature, SWIPT has been generally studied under the ideal (and unrealistic) assumption of linear energy harvesting, which means that the energy (or power) conversion efficiency of the energy harvesting circuit is constant over the infinitely wide range of the input RF power. However, as validated in many field measurements, the energy conversion efficiency of the actual energy harvesting circuit highly depends on the input RF power level. Specifically, due to the nonlinearities of the practical diode such as the turn-on voltage and saturation issue, the linearity assumption of the energy harvesting circuitry is significantly deviated in practical situations. In this talk, we present the recent research results on SWIPT considering the nonlinear energy harvesting. In particular, we will talk about the fundamental performance limit of SWIPT in terms of rate-energy (R-E) trade-off, the approach of using multiple energy harvesting circuits, mode selection between energy harvesting and information transfer, and optimal dynamic power allocation for SWIPT.

Speaker Biography:

Il-Min Kim received the B.S. degree in electronics engineering from Yonsei University, Seoul, Korea, in 1996, and the M.S. and Ph.D. degrees in electrical engineering from the Korea Advanced Institute of Science and Technology (KAIST), Taejon, Korea, in 1998 and 2001, respectively. From October 2001 to August 2002 he was with the Dept. of Electrical Engineering and Computer Sciences (EECS) at Massachusetts Institute of Technology (MIT), Cambridge, USA, and from September 2002 to June 2003 he was with the Dept. of Electrical Engineering at Harvard University, Cambridge, USA, as a Postdoctoral Research Fellow. In 2003, he joined the Dept. of Electrical and Computer Engineering at Queen’s University, Kingston, Canada, and he is currently a Professor. His research interests include machine (deep) learning for various systems (especially with sensors), IoT (and IoE), signal processing for IoT, (mobile) crowd sensing, fog/cloud networks, communication security, blockchain for wireless communications, physical layer security, energy harvesting and SWIPT, compressive sensing, military communications and Radars, and 5th generation (5G) and beyond 5G wireless communications systems. He holds a number of patents either issued or pending in U.S., Japan, Germany, and Korea.